"Everything that can be invented has been invented"
This quote was from Charles Duell, Head of the US Patent office in 1889 who confidently believed that 'everything that can be invented, has been invented'. Poor guy. This was way back before any Metaverse, Crypto or even Fintech! 🤔
I must admit, sometimes I summon my inner Duell and think 'What is next? Innovation is slowing, it can't continue much longer. We have arrived'. Is it just me?
So when something novel pops up, it is always a pleasure to dig deeper, spread the word and stop my inner Duell-ing.
And so this brings me to some amazing marketplaces supplying produce directly from farmers in developing markets to restaurants.
This is niche - hence my emphasis on innovation and invention - but it is growing and I think points the way for other categories. In the countries where these platforms are just starting, the fragmented nature of the market actually makes it a lucrative sweet-spot for a platform business that can add real value.
Million of Producers ↔️ Millions of Consumers ✅
What also fascinates me about the companies I discuss below, are the elements of the consumer to manufacturing (C2M) trend in Food and Agriculture, as exemplified by Pinduoduo in China. Both embrace data to manage their inventory risk.
So let's talk about two specific companies who are working hard on 'the everything store for restaurants':
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The Frubana Factor
Frubana are the category defining company and have become one of many darlings in the booming Latin American Fintech scene.
They have just closed a Series B for $65m based on their model to be the 'everything store for restaurants' in the region. This total market buys produce worth $100bn per annum converting it into $300bn in sales.
This proposition is truly unique and testament to how use cases can be developed quickly and scaled even quicker once key assumptions are validated.
Jobs to be Done
Like most entrepreneurs it seems that Fabián Gomez, founder of Frubana, knew there was an opportunity, but just couldn't quite figure out the problem to solve for his marketplace vision. This is a classical marketplace dilemma, around since the days of Charles Duell. Which side should it serve and how? Was it for farmers or for the restaurants?
Initially, Frubana took option 1 and almost flopped with just a few dozen downloads of a produce marketing app for farmers. But as things changed, the problem become more evident ➡️ the reliable supply of fresh produce to restaurants when they needed it. It was the restaurant side that needed attention.
By switching focus to the buyer side of the platform, they unlocked the opportunity by building the platform where restaurants could buy, as opposed to where farmers could sell.
To solve the problem of reliable supply, this meant they needed to guarantee inventory as much as possible and to actually source the inventory from farmers and local markets when necessary.
Obviously, securing and paying for inventory is cash intensive, especially in new markets. However, similar to the C2M model, I discussed previously, Frubana turned to their data to create a forecasting model which would help them smooth out any inventory excess or shortages.
The data started to yield insights immediately. For example, each month had significant variations in traffic to restaurants, depending on salary payments, holidays or even a local football match taking place. Unsurprisingly, footfall data also became a reliable predictor of demand in the coming days, which Frubana came to rely on and use in their forecast models.
This data driven approach allowed them to confidently buy stock in advance of orders which meant they could fulfil orders quickly and keep wastage to less than 2%.
Less than 2% - think about that. In developing countries, food spoilage runs as high 50% in some categories and globally roughly one-third of all food produced is lost, according to the FAO.
Less than 2%. 👏
What is next?
According to this interview, more geographical expansion but also a move into direct financial services and a SaaS model for managing the sales side for restaurants.
Interestingly, Vendease (below) have already made a transition into financial services and embedded finance.
Y Combinator backed Vendease are another promising company tackling a similar problem, this time in Nigeria. This market, like those in Latin America, has fragmented dynamics allowing the proliferation of the 'Amazon Prime for Restaurants' model, as co-founder Tunde Kara calls it, when we caught up to discuss this.
Their inspiration came when the founders noted several restaurants close and discovered that this was due to an inability to buy - and consistently buy - basic products, despite markets being well stocked 🤷♂️.
The SKU problem
At the heart of the problem Vendease identified, similar to Frubana, were 100's of products that needed to be bought by restaurants on a regular basis.
The supply of these products was inconsistent as middlemen frequently went out of business or lost money due to the fragmented market and were at the wrong end of long, onerous payment terms.
In addition, logistical challenges between markets and restaurants in crowded cities such as Lagos compounded problems for buyers as they could have up to 100 suppliers for a small family run restaurant. Figuring out who is owed what becomes a full time job pretty quickly.
Obviously, over time this problem compounds and the lengthy cash cycle means sellers compensate by hiking margins up to 100-200% according to Kara.
This was the Vendease call to action and their marketplace approach has managed to attract not only the smaller restaurant segment of the market, as Frubana have, but also some of the medium and large international chains operating in Lagos, Abuja and Ibadan, with now over 1000 businesses onboarded.
Again with the data
Over time the Lagos based start up has gathered enough data to refine it's own prediction engine for orders. This allowed the company to reach offtake agreements with some of its major customers in the hospitality sector and negotiating expedited payment terms, within 48 hours.
This has allowed the startup to retain customers by demonstrating convenience, transparency and access to the data insights for its users.
In fact, according to Kara, the platform can predict demand for some SKU's up to 3 months in advance and for high turnover products, forecasting the next 12 hours is also possible.
But while it focuses on the demand side, it notes the market issues on the supply side are still problematic. Generally, in their market segment, demand outweighs supply significantly, and so working with actual producers at farm level has become part of their mission to address the imbalance.
"What started out as a procurement tool has now evolved into a data led fintech tool" serving both sides of the market he notes.
For me, this demonstrates the significance of the C2M model for the Food and Agriculture sector - it can start to give firm price, quality and quantity signals to growers. These signals reduce risk and encourage commercial growth.
Reaching further upstream has opened up some interesting fintech related opportunities already for the Vendease team. In 2020, the platform entered into a project with Grow Africa, which set out to provide financing of up to $3m upstream for small farmers who wanted to supply the Vendease marketplace.
As Kara notes, this will allowed the company to attract many small and medium sized producers who can rely on Vendease for timely payments and production financing. Vendease is targeting 10,000 smallholder producers using this facility.
This demonstrates where the magic of the C2M model happens.
Demand + Data => Bankability
The platform effectively becomes a credible offtaker in a structured trade finance transaction.
When Vendease start to raise capital in early 2022, this is one area they want to expand.
Pardon the pun 😛
These companies are quite compelling examples of where niches are targeted, landed and then expanded.
✅ C2M looks compelling for developing markets, especially for the market demand and price signalling.
✅ There is often a focus on improving agricultural yields in the developing world, which certainly needs to happen, but not as much attention gets paid to the end market linkages. (India might be an exception in this regard.) Without a
proper better market mechanism higher yields just means higher waste.
The best thing is there are dozens of niches in the Agri sector globally that can use similar models to embed financial services. Maybe in transport, warehousing or other produce sectors such as aquaculture or dairy.
In my next issue, I will talk to one such company in the US who are certainly developing a promising trove of data.
Thank you for reading and don't forget to subscribe ⤵️